mirror of
https://github.com/meilisearch/meilisearch.git
synced 2024-12-01 09:34:58 +08:00
Merge fdcd483740
into c1d8ee2a8d
This commit is contained in:
commit
e78a76e15c
@ -627,6 +627,8 @@ impl IndexScheduler {
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self.breakpoint(crate::Breakpoint::InsideProcessBatch);
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}
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let index_uid = batch.index_uid().map(String::from);
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match batch {
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Batch::TaskCancelation { mut task, previous_started_at, previous_processing_tasks } => {
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// 1. Retrieve the tasks that matched the query at enqueue-time.
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@ -765,7 +767,9 @@ impl IndexScheduler {
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let index = self.index_mapper.index(&rtxn, name)?;
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let dst = temp_snapshot_dir.path().join("indexes").join(uuid.to_string());
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fs::create_dir_all(&dst)?;
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index.copy_to_file(dst.join("data.mdb"), CompactionOption::Enabled)?;
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index
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.copy_to_file(dst.join("data.mdb"), CompactionOption::Enabled)
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.map_err(|e| Error::from_milli(e, Some(name.to_string())))?;
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}
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drop(rtxn);
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@ -843,7 +847,6 @@ impl IndexScheduler {
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let (_, mut t) = ret?;
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let status = t.status;
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let content_file = t.content_uuid();
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// In the case we're dumping ourselves we want to be marked as finished
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// to not loop over ourselves indefinitely.
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if t.uid == task.uid {
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@ -866,19 +869,21 @@ impl IndexScheduler {
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if status == Status::Enqueued {
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let content_file = self.file_store.get_update(content_file)?;
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let reader = DocumentsBatchReader::from_reader(content_file)
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.map_err(milli::Error::from)?;
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let reader =
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DocumentsBatchReader::from_reader(content_file).map_err(|e| {
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Error::Milli { error: e.into(), index_name: index_uid.clone() }
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})?;
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let (mut cursor, documents_batch_index) =
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reader.into_cursor_and_fields_index();
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while let Some(doc) =
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cursor.next_document().map_err(milli::Error::from)?
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{
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dump_content_file.push_document(&obkv_to_object(
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&doc,
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&documents_batch_index,
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)?)?;
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while let Some(doc) = cursor.next_document().map_err(|e| {
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Error::Milli { error: e.into(), index_name: index_uid.clone() }
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})? {
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dump_content_file.push_document(
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&obkv_to_object(&doc, &documents_batch_index)
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.map_err(|e| Error::from_milli(e, index_uid.clone()))?,
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)?;
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}
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dump_content_file.flush()?;
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}
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@ -892,27 +897,41 @@ impl IndexScheduler {
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let metadata = IndexMetadata {
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uid: uid.to_owned(),
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primary_key: index.primary_key(&rtxn)?.map(String::from),
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created_at: index.created_at(&rtxn)?,
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updated_at: index.updated_at(&rtxn)?,
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created_at: index
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.created_at(&rtxn)
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?,
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updated_at: index
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.updated_at(&rtxn)
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?,
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};
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let mut index_dumper = dump.create_index(uid, &metadata)?;
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let fields_ids_map = index.fields_ids_map(&rtxn)?;
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let all_fields: Vec<_> = fields_ids_map.iter().map(|(id, _)| id).collect();
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let embedding_configs = index.embedding_configs(&rtxn)?;
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let embedding_configs = index
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.embedding_configs(&rtxn)
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
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let documents = index
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.all_documents(&rtxn)
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
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// 3.1. Dump the documents
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for ret in index.all_documents(&rtxn)? {
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for ret in documents {
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if self.must_stop_processing.get() {
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return Err(Error::AbortedTask);
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}
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let (id, doc) = ret?;
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let (id, doc) =
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ret.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
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let mut document = milli::obkv_to_json(&all_fields, &fields_ids_map, doc)?;
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let mut document =
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milli::obkv_to_json(&all_fields, &fields_ids_map, doc)
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
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'inject_vectors: {
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let embeddings = index.embeddings(&rtxn, id)?;
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let embeddings = index
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.embeddings(&rtxn, id)
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
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if embeddings.is_empty() {
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break 'inject_vectors;
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@ -923,22 +942,24 @@ impl IndexScheduler {
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.or_insert(serde_json::Value::Object(Default::default()));
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let serde_json::Value::Object(vectors) = vectors else {
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return Err(milli::Error::UserError(
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milli::UserError::InvalidVectorsMapType {
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document_id: {
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if let Ok(Some(Ok(index))) = index
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.external_id_of(&rtxn, std::iter::once(id))
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.map(|it| it.into_iter().next())
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{
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index
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} else {
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format!("internal docid={id}")
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}
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return Err(Error::from_milli(
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milli::Error::UserError(
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milli::UserError::InvalidVectorsMapType {
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document_id: {
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if let Ok(Some(Ok(index))) = index
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.external_id_of(&rtxn, std::iter::once(id))
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.map(|it| it.into_iter().next())
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{
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index
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} else {
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format!("internal docid={id}")
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}
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},
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value: vectors.clone(),
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},
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value: vectors.clone(),
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},
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)
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.into());
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),
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Some(uid.to_string()),
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));
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};
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for (embedder_name, embeddings) in embeddings {
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@ -968,7 +989,8 @@ impl IndexScheduler {
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index,
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&rtxn,
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meilisearch_types::settings::SecretPolicy::RevealSecrets,
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)?;
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)
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
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index_dumper.settings(&settings)?;
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Ok(())
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})?;
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@ -1018,7 +1040,8 @@ impl IndexScheduler {
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// the entire batch.
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let res = || -> Result<()> {
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let index_rtxn = index.read_txn()?;
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let stats = crate::index_mapper::IndexStats::new(&index, &index_rtxn)?;
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let stats = crate::index_mapper::IndexStats::new(&index, &index_rtxn)
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.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
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let mut wtxn = self.env.write_txn()?;
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self.index_mapper.store_stats_of(&mut wtxn, &index_uid, &stats)?;
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wtxn.commit()?;
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@ -1057,10 +1080,12 @@ impl IndexScheduler {
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);
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builder.set_primary_key(primary_key);
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let must_stop_processing = self.must_stop_processing.clone();
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builder.execute(
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|indexing_step| tracing::debug!(update = ?indexing_step),
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|| must_stop_processing.get(),
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)?;
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builder
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.execute(
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|indexing_step| tracing::debug!(update = ?indexing_step),
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|| must_stop_processing.get(),
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)
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.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
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index_wtxn.commit()?;
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}
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@ -1077,7 +1102,8 @@ impl IndexScheduler {
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let res = || -> Result<()> {
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let mut wtxn = self.env.write_txn()?;
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let index_rtxn = index.read_txn()?;
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let stats = crate::index_mapper::IndexStats::new(&index, &index_rtxn)?;
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let stats = crate::index_mapper::IndexStats::new(&index, &index_rtxn)
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.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
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self.index_mapper.store_stats_of(&mut wtxn, &index_uid, &stats)?;
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wtxn.commit()?;
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Ok(())
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@ -1100,7 +1126,9 @@ impl IndexScheduler {
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let number_of_documents = || -> Result<u64> {
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let index = self.index_mapper.index(&wtxn, &index_uid)?;
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let index_rtxn = index.read_txn()?;
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Ok(index.number_of_documents(&index_rtxn)?)
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index
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.number_of_documents(&index_rtxn)
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.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))
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}()
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.unwrap_or_default();
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@ -1219,8 +1247,10 @@ impl IndexScheduler {
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operation: IndexOperation,
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) -> Result<Vec<Task>> {
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match operation {
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IndexOperation::DocumentClear { mut tasks, .. } => {
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let count = milli::update::ClearDocuments::new(index_wtxn, index).execute()?;
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IndexOperation::DocumentClear { index_uid, mut tasks, .. } => {
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let count = milli::update::ClearDocuments::new(index_wtxn, index)
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.execute()
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.map_err(|e| Error::from_milli(e, Some(index_uid)))?;
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let mut first_clear_found = false;
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for task in &mut tasks {
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@ -1240,7 +1270,7 @@ impl IndexScheduler {
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Ok(tasks)
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}
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IndexOperation::DocumentOperation {
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index_uid: _,
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index_uid,
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primary_key,
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method,
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documents_counts: _,
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@ -1258,10 +1288,11 @@ impl IndexScheduler {
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// but to a different value, we can make the whole batch fail.
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Some(pk) => {
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if primary_key != pk {
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return Err(milli::Error::from(
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milli::UserError::PrimaryKeyCannotBeChanged(pk.to_string()),
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)
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.into());
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return Err(Error::from_milli(
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milli::UserError::PrimaryKeyCannotBeChanged(pk.to_string())
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.into(),
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Some(index_uid.clone()),
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));
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}
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}
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// if the primary key was set and there was no primary key set for this index
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@ -1270,10 +1301,12 @@ impl IndexScheduler {
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let mut builder =
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milli::update::Settings::new(index_wtxn, index, indexer_config);
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builder.set_primary_key(primary_key);
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builder.execute(
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|indexing_step| tracing::debug!(update = ?indexing_step),
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|| must_stop_processing.clone().get(),
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)?;
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builder
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.execute(
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|indexing_step| tracing::debug!(update = ?indexing_step),
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|| must_stop_processing.clone().get(),
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)
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.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
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primary_key_has_been_set = true;
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}
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}
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@ -1281,9 +1314,11 @@ impl IndexScheduler {
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let config = IndexDocumentsConfig { update_method: method, ..Default::default() };
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let embedder_configs = index.embedding_configs(index_wtxn)?;
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let embedder_configs = index
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.embedding_configs(index_wtxn)
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.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
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// TODO: consider Arc'ing the map too (we only need read access + we'll be cloning it multiple times, so really makes sense)
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let embedders = self.embedders(embedder_configs)?;
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let embedders = self.embedders(index_uid.clone(), embedder_configs)?;
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let mut builder = milli::update::IndexDocuments::new(
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index_wtxn,
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@ -1292,15 +1327,20 @@ impl IndexScheduler {
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config,
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|indexing_step| tracing::trace!(?indexing_step, "Update"),
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|| must_stop_processing.get(),
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)?;
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)
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.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
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|
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for (operation, task) in operations.into_iter().zip(tasks.iter_mut()) {
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match operation {
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DocumentOperation::Add(content_uuid) => {
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let content_file = self.file_store.get_update(content_uuid)?;
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||||
let reader = DocumentsBatchReader::from_reader(content_file)
|
||||
.map_err(milli::Error::from)?;
|
||||
let (new_builder, user_result) = builder.add_documents(reader)?;
|
||||
let reader =
|
||||
DocumentsBatchReader::from_reader(content_file).map_err(|e| {
|
||||
Error::from_milli(e.into(), Some(index_uid.clone()))
|
||||
})?;
|
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let (new_builder, user_result) = builder
|
||||
.add_documents(reader)
|
||||
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
|
||||
builder = new_builder;
|
||||
|
||||
builder = builder.with_embedders(embedders.clone());
|
||||
@ -1336,8 +1376,9 @@ impl IndexScheduler {
|
||||
}
|
||||
}
|
||||
DocumentOperation::Delete(document_ids) => {
|
||||
let (new_builder, user_result) =
|
||||
builder.remove_documents(document_ids)?;
|
||||
let (new_builder, user_result) = builder
|
||||
.remove_documents(document_ids)
|
||||
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
|
||||
builder = new_builder;
|
||||
// Uses Invariant: remove documents actually always returns Ok for the inner result
|
||||
let count = user_result.unwrap();
|
||||
@ -1361,7 +1402,8 @@ impl IndexScheduler {
|
||||
}
|
||||
|
||||
if !tasks.iter().all(|res| res.error.is_some()) {
|
||||
let addition = builder.execute()?;
|
||||
let addition =
|
||||
builder.execute().map_err(|e| Error::from_milli(e, Some(index_uid)))?;
|
||||
tracing::info!(indexing_result = ?addition, processed_in = ?started_processing_at.elapsed(), "document indexing done");
|
||||
} else if primary_key_has_been_set {
|
||||
// Everything failed but we've set a primary key.
|
||||
@ -1369,15 +1411,17 @@ impl IndexScheduler {
|
||||
let mut builder =
|
||||
milli::update::Settings::new(index_wtxn, index, indexer_config);
|
||||
builder.reset_primary_key();
|
||||
builder.execute(
|
||||
|indexing_step| tracing::trace!(update = ?indexing_step),
|
||||
|| must_stop_processing.clone().get(),
|
||||
)?;
|
||||
builder
|
||||
.execute(
|
||||
|indexing_step| tracing::trace!(update = ?indexing_step),
|
||||
|| must_stop_processing.clone().get(),
|
||||
)
|
||||
.map_err(|e| Error::from_milli(e, Some(index_uid)))?;
|
||||
}
|
||||
|
||||
Ok(tasks)
|
||||
}
|
||||
IndexOperation::DocumentEdition { mut task, .. } => {
|
||||
IndexOperation::DocumentEdition { index_uid, mut task } => {
|
||||
let (filter, context, function) =
|
||||
if let KindWithContent::DocumentEdition {
|
||||
filter_expr, context, function, ..
|
||||
@ -1395,7 +1439,14 @@ impl IndexScheduler {
|
||||
self.index_mapper.indexer_config(),
|
||||
self.must_stop_processing.clone(),
|
||||
index,
|
||||
);
|
||||
)
|
||||
.map_err(|err| match err {
|
||||
milli::Error::UserError(milli::UserError::InvalidFilter(_)) => {
|
||||
Error::from_milli(err, Some(index_uid.clone()))
|
||||
.with_custom_error_code(Code::InvalidDocumentFilter)
|
||||
}
|
||||
e => Error::from_milli(e, Some(index_uid.clone())),
|
||||
});
|
||||
let (original_filter, context, function) = if let Some(Details::DocumentEdition {
|
||||
original_filter,
|
||||
context,
|
||||
@ -1435,7 +1486,7 @@ impl IndexScheduler {
|
||||
|
||||
Ok(vec![task])
|
||||
}
|
||||
IndexOperation::DocumentDeletion { mut tasks, index_uid: _ } => {
|
||||
IndexOperation::DocumentDeletion { mut tasks, index_uid } => {
|
||||
let mut to_delete = RoaringBitmap::new();
|
||||
let external_documents_ids = index.external_documents_ids();
|
||||
|
||||
@ -1456,7 +1507,7 @@ impl IndexScheduler {
|
||||
deleted_documents: Some(will_be_removed),
|
||||
});
|
||||
}
|
||||
KindWithContent::DocumentDeletionByFilter { index_uid: _, filter_expr } => {
|
||||
KindWithContent::DocumentDeletionByFilter { index_uid, filter_expr } => {
|
||||
let before = to_delete.len();
|
||||
let filter = match Filter::from_json(filter_expr) {
|
||||
Ok(filter) => filter,
|
||||
@ -1467,7 +1518,7 @@ impl IndexScheduler {
|
||||
milli::Error::UserError(
|
||||
milli::UserError::InvalidFilterExpression { .. },
|
||||
) => Some(
|
||||
Error::from(err)
|
||||
Error::from_milli(err, Some(index_uid.clone()))
|
||||
.with_custom_error_code(Code::InvalidDocumentFilter)
|
||||
.into(),
|
||||
),
|
||||
@ -1481,9 +1532,9 @@ impl IndexScheduler {
|
||||
filter.evaluate(index_wtxn, index).map_err(|err| match err {
|
||||
milli::Error::UserError(
|
||||
milli::UserError::InvalidFilter(_),
|
||||
) => Error::from(err)
|
||||
) => Error::from_milli(err, Some(index_uid.clone()))
|
||||
.with_custom_error_code(Code::InvalidDocumentFilter),
|
||||
e => e.into(),
|
||||
e => Error::from_milli(e, Some(index_uid.clone())),
|
||||
});
|
||||
match candidates {
|
||||
Ok(candidates) => to_delete |= candidates,
|
||||
@ -1522,17 +1573,21 @@ impl IndexScheduler {
|
||||
config,
|
||||
|indexing_step| tracing::debug!(update = ?indexing_step),
|
||||
|| must_stop_processing.get(),
|
||||
)?;
|
||||
)
|
||||
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
|
||||
|
||||
let (new_builder, _count) =
|
||||
builder.remove_documents_from_db_no_batch(&to_delete)?;
|
||||
builder
|
||||
.remove_documents_from_db_no_batch(&to_delete)
|
||||
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
|
||||
builder = new_builder;
|
||||
|
||||
let _ = builder.execute()?;
|
||||
let _ =
|
||||
builder.execute().map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
|
||||
|
||||
Ok(tasks)
|
||||
}
|
||||
IndexOperation::Settings { index_uid: _, settings, mut tasks } => {
|
||||
IndexOperation::Settings { index_uid, settings, mut tasks } => {
|
||||
let indexer_config = self.index_mapper.indexer_config();
|
||||
let mut builder = milli::update::Settings::new(index_wtxn, index, indexer_config);
|
||||
|
||||
@ -1547,10 +1602,12 @@ impl IndexScheduler {
|
||||
}
|
||||
|
||||
let must_stop_processing = self.must_stop_processing.clone();
|
||||
builder.execute(
|
||||
|indexing_step| tracing::debug!(update = ?indexing_step),
|
||||
|| must_stop_processing.get(),
|
||||
)?;
|
||||
builder
|
||||
.execute(
|
||||
|indexing_step| tracing::debug!(update = ?indexing_step),
|
||||
|| must_stop_processing.get(),
|
||||
)
|
||||
.map_err(|e| Error::from_milli(e, Some(index_uid)))?;
|
||||
|
||||
Ok(tasks)
|
||||
}
|
||||
@ -1742,16 +1799,11 @@ fn edit_documents_by_function<'a>(
|
||||
indexer_config: &IndexerConfig,
|
||||
must_stop_processing: MustStopProcessing,
|
||||
index: &'a Index,
|
||||
) -> Result<(u64, u64)> {
|
||||
) -> milli::Result<(u64, u64)> {
|
||||
let candidates = match filter.as_ref().map(Filter::from_json) {
|
||||
Some(Ok(Some(filter))) => filter.evaluate(wtxn, index).map_err(|err| match err {
|
||||
milli::Error::UserError(milli::UserError::InvalidFilter(_)) => {
|
||||
Error::from(err).with_custom_error_code(Code::InvalidDocumentFilter)
|
||||
}
|
||||
e => e.into(),
|
||||
})?,
|
||||
Some(Ok(Some(filter))) => filter.evaluate(wtxn, index)?,
|
||||
None | Some(Ok(None)) => index.documents_ids(wtxn)?,
|
||||
Some(Err(e)) => return Err(e.into()),
|
||||
Some(Err(e)) => return Err(e),
|
||||
};
|
||||
|
||||
let config = IndexDocumentsConfig {
|
||||
|
@ -117,8 +117,11 @@ pub enum Error {
|
||||
Dump(#[from] dump::Error),
|
||||
#[error(transparent)]
|
||||
Heed(#[from] heed::Error),
|
||||
#[error(transparent)]
|
||||
Milli(#[from] milli::Error),
|
||||
#[error("{}", match .index_name {
|
||||
Some(name) if !name.is_empty() => format!("Index `{}`: {error}", name),
|
||||
_ => format!("{error}")
|
||||
})]
|
||||
Milli { error: milli::Error, index_name: Option<String> },
|
||||
#[error("An unexpected crash occurred when processing the task.")]
|
||||
ProcessBatchPanicked,
|
||||
#[error(transparent)]
|
||||
@ -183,7 +186,7 @@ impl Error {
|
||||
| Error::AbortedTask
|
||||
| Error::Dump(_)
|
||||
| Error::Heed(_)
|
||||
| Error::Milli(_)
|
||||
| Error::Milli { .. }
|
||||
| Error::ProcessBatchPanicked
|
||||
| Error::FileStore(_)
|
||||
| Error::IoError(_)
|
||||
@ -202,6 +205,10 @@ impl Error {
|
||||
pub fn with_custom_error_code(self, code: Code) -> Self {
|
||||
Self::WithCustomErrorCode(code, Box::new(self))
|
||||
}
|
||||
|
||||
pub fn from_milli(error: milli::Error, index_name: Option<String>) -> Self {
|
||||
Self::Milli { error, index_name }
|
||||
}
|
||||
}
|
||||
|
||||
impl ErrorCode for Error {
|
||||
@ -227,7 +234,7 @@ impl ErrorCode for Error {
|
||||
// TODO: not sure of the Code to use
|
||||
Error::NoSpaceLeftInTaskQueue => Code::NoSpaceLeftOnDevice,
|
||||
Error::Dump(e) => e.error_code(),
|
||||
Error::Milli(e) => e.error_code(),
|
||||
Error::Milli { error, .. } => error.error_code(),
|
||||
Error::ProcessBatchPanicked => Code::Internal,
|
||||
Error::Heed(e) => e.error_code(),
|
||||
Error::HeedTransaction(e) => e.error_code(),
|
||||
|
@ -3,14 +3,13 @@ use std::path::Path;
|
||||
use std::time::Duration;
|
||||
|
||||
use meilisearch_types::heed::{EnvClosingEvent, EnvFlags, EnvOpenOptions};
|
||||
use meilisearch_types::milli::Index;
|
||||
use meilisearch_types::milli::{Index, Result};
|
||||
use time::OffsetDateTime;
|
||||
use uuid::Uuid;
|
||||
|
||||
use super::IndexStatus::{self, Available, BeingDeleted, Closing, Missing};
|
||||
use crate::clamp_to_page_size;
|
||||
use crate::lru::{InsertionOutcome, LruMap};
|
||||
use crate::{clamp_to_page_size, Result};
|
||||
|
||||
/// Keep an internally consistent view of the open indexes in memory.
|
||||
///
|
||||
/// This view is made of an LRU cache that will evict the least frequently used indexes when new indexes are opened.
|
||||
|
@ -3,8 +3,13 @@ use std::sync::{Arc, RwLock};
|
||||
use std::time::Duration;
|
||||
use std::{fs, thread};
|
||||
|
||||
use self::index_map::IndexMap;
|
||||
use self::IndexStatus::{Available, BeingDeleted, Closing, Missing};
|
||||
use crate::uuid_codec::UuidCodec;
|
||||
use crate::{Error, Result};
|
||||
use meilisearch_types::heed::types::{SerdeJson, Str};
|
||||
use meilisearch_types::heed::{Database, Env, RoTxn, RwTxn};
|
||||
use meilisearch_types::milli;
|
||||
use meilisearch_types::milli::update::IndexerConfig;
|
||||
use meilisearch_types::milli::{FieldDistribution, Index};
|
||||
use serde::{Deserialize, Serialize};
|
||||
@ -12,11 +17,6 @@ use time::OffsetDateTime;
|
||||
use tracing::error;
|
||||
use uuid::Uuid;
|
||||
|
||||
use self::index_map::IndexMap;
|
||||
use self::IndexStatus::{Available, BeingDeleted, Closing, Missing};
|
||||
use crate::uuid_codec::UuidCodec;
|
||||
use crate::{Error, Result};
|
||||
|
||||
mod index_map;
|
||||
|
||||
const INDEX_MAPPING: &str = "index-mapping";
|
||||
@ -121,7 +121,7 @@ impl IndexStats {
|
||||
/// # Parameters
|
||||
///
|
||||
/// - rtxn: a RO transaction for the index, obtained from `Index::read_txn()`.
|
||||
pub fn new(index: &Index, rtxn: &RoTxn) -> Result<Self> {
|
||||
pub fn new(index: &Index, rtxn: &RoTxn) -> milli::Result<Self> {
|
||||
Ok(IndexStats {
|
||||
number_of_documents: index.number_of_documents(rtxn)?,
|
||||
database_size: index.on_disk_size()?,
|
||||
@ -183,13 +183,18 @@ impl IndexMapper {
|
||||
// Error if the UUIDv4 somehow already exists in the map, since it should be fresh.
|
||||
// This is very unlikely to happen in practice.
|
||||
// TODO: it would be better to lazily create the index. But we need an Index::open function for milli.
|
||||
let index = self.index_map.write().unwrap().create(
|
||||
&uuid,
|
||||
&index_path,
|
||||
date,
|
||||
self.enable_mdb_writemap,
|
||||
self.index_base_map_size,
|
||||
)?;
|
||||
let index = self
|
||||
.index_map
|
||||
.write()
|
||||
.unwrap()
|
||||
.create(
|
||||
&uuid,
|
||||
&index_path,
|
||||
date,
|
||||
self.enable_mdb_writemap,
|
||||
self.index_base_map_size,
|
||||
)
|
||||
.map_err(|e| Error::from_milli(e, Some(uuid.to_string())))?;
|
||||
|
||||
wtxn.commit()?;
|
||||
|
||||
@ -357,7 +362,9 @@ impl IndexMapper {
|
||||
};
|
||||
let index_path = self.base_path.join(uuid.to_string());
|
||||
// take the lock to reopen the environment.
|
||||
reopen.reopen(&mut self.index_map.write().unwrap(), &index_path)?;
|
||||
reopen
|
||||
.reopen(&mut self.index_map.write().unwrap(), &index_path)
|
||||
.map_err(|e| Error::from_milli(e, Some(uuid.to_string())))?;
|
||||
continue;
|
||||
}
|
||||
BeingDeleted => return Err(Error::IndexNotFound(name.to_string())),
|
||||
@ -372,13 +379,15 @@ impl IndexMapper {
|
||||
Missing => {
|
||||
let index_path = self.base_path.join(uuid.to_string());
|
||||
|
||||
break index_map.create(
|
||||
&uuid,
|
||||
&index_path,
|
||||
None,
|
||||
self.enable_mdb_writemap,
|
||||
self.index_base_map_size,
|
||||
)?;
|
||||
break index_map
|
||||
.create(
|
||||
&uuid,
|
||||
&index_path,
|
||||
None,
|
||||
self.enable_mdb_writemap,
|
||||
self.index_base_map_size,
|
||||
)
|
||||
.map_err(|e| Error::from_milli(e, Some(uuid.to_string())))?;
|
||||
}
|
||||
Available(index) => break index,
|
||||
Closing(_) => {
|
||||
@ -460,6 +469,7 @@ impl IndexMapper {
|
||||
let index = self.index(rtxn, index_uid)?;
|
||||
let index_rtxn = index.read_txn()?;
|
||||
IndexStats::new(&index, &index_rtxn)
|
||||
.map_err(|e| Error::from_milli(e, Some(uuid.to_string())))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
@ -1225,9 +1225,10 @@ impl IndexScheduler {
|
||||
tracing::info!("A batch of tasks was successfully completed with {success} successful tasks and {failure} failed tasks.");
|
||||
}
|
||||
// If we have an abortion error we must stop the tick here and re-schedule tasks.
|
||||
Err(Error::Milli(milli::Error::InternalError(
|
||||
milli::InternalError::AbortedIndexation,
|
||||
)))
|
||||
Err(Error::Milli {
|
||||
error: milli::Error::InternalError(milli::InternalError::AbortedIndexation),
|
||||
..
|
||||
})
|
||||
| Err(Error::AbortedTask) => {
|
||||
#[cfg(test)]
|
||||
self.breakpoint(Breakpoint::AbortedIndexation);
|
||||
@ -1246,9 +1247,10 @@ impl IndexScheduler {
|
||||
// 2. close the associated environment
|
||||
// 3. resize it
|
||||
// 4. re-schedule tasks
|
||||
Err(Error::Milli(milli::Error::UserError(
|
||||
milli::UserError::MaxDatabaseSizeReached,
|
||||
))) if index_uid.is_some() => {
|
||||
Err(Error::Milli {
|
||||
error: milli::Error::UserError(milli::UserError::MaxDatabaseSizeReached),
|
||||
..
|
||||
}) if index_uid.is_some() => {
|
||||
// fixme: add index_uid to match to avoid the unwrap
|
||||
let index_uid = index_uid.unwrap();
|
||||
// fixme: handle error more gracefully? not sure when this could happen
|
||||
@ -1485,6 +1487,7 @@ impl IndexScheduler {
|
||||
// TODO: consider using a type alias or a struct embedder/template
|
||||
pub fn embedders(
|
||||
&self,
|
||||
index_uid: String,
|
||||
embedding_configs: Vec<IndexEmbeddingConfig>,
|
||||
) -> Result<EmbeddingConfigs> {
|
||||
let res: Result<_> = embedding_configs
|
||||
@ -1495,8 +1498,12 @@ impl IndexScheduler {
|
||||
config: milli::vector::EmbeddingConfig { embedder_options, prompt, quantized },
|
||||
..
|
||||
}| {
|
||||
let prompt =
|
||||
Arc::new(prompt.try_into().map_err(meilisearch_types::milli::Error::from)?);
|
||||
let prompt = Arc::new(
|
||||
prompt
|
||||
.try_into()
|
||||
.map_err(meilisearch_types::milli::Error::from)
|
||||
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?,
|
||||
);
|
||||
// optimistically return existing embedder
|
||||
{
|
||||
let embedders = self.embedders.read().unwrap();
|
||||
@ -1512,7 +1519,8 @@ impl IndexScheduler {
|
||||
let embedder = Arc::new(
|
||||
Embedder::new(embedder_options.clone())
|
||||
.map_err(meilisearch_types::milli::vector::Error::from)
|
||||
.map_err(meilisearch_types::milli::Error::from)?,
|
||||
.map_err(meilisearch_types::milli::Error::from)
|
||||
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?,
|
||||
);
|
||||
{
|
||||
let mut embedders = self.embedders.write().unwrap();
|
||||
@ -5214,7 +5222,7 @@ mod tests {
|
||||
insta::assert_json_snapshot!(simple_hf_config.embedder_options);
|
||||
let simple_hf_name = name.clone();
|
||||
|
||||
let configs = index_scheduler.embedders(configs).unwrap();
|
||||
let configs = index_scheduler.embedders("doggos".to_string(), configs).unwrap();
|
||||
let (hf_embedder, _, _) = configs.get(&simple_hf_name).unwrap();
|
||||
let beagle_embed = hf_embedder.embed_one(S("Intel the beagle best doggo")).unwrap();
|
||||
let lab_embed = hf_embedder.embed_one(S("Max the lab best doggo")).unwrap();
|
||||
|
@ -9,8 +9,8 @@ source: index-scheduler/src/lib.rs
|
||||
0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: Set({"catto"}), sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: NotSet, search_cutoff_ms: NotSet, localized_attributes: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: Set({"catto"}), sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: NotSet, search_cutoff_ms: NotSet, localized_attributes: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
|
||||
1 {uid: 1, status: succeeded, details: { received_documents: 3, indexed_documents: Some(3) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 3, allow_index_creation: true }}
|
||||
2 {uid: 2, status: succeeded, details: { received_document_ids: 1, deleted_documents: Some(1) }, kind: DocumentDeletion { index_uid: "doggos", documents_ids: ["1"] }}
|
||||
3 {uid: 3, status: failed, error: ResponseError { code: 200, message: "Invalid type for filter subexpression: expected: String, Array, found: true.", error_code: "invalid_document_filter", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#invalid_document_filter" }, details: { original_filter: true, deleted_documents: Some(0) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: Bool(true) }}
|
||||
4 {uid: 4, status: failed, error: ResponseError { code: 200, message: "Attribute `id` is not filterable. Available filterable attributes are: `catto`.\n1:3 id = 2", error_code: "invalid_document_filter", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#invalid_document_filter" }, details: { original_filter: "id = 2", deleted_documents: Some(0) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: String("id = 2") }}
|
||||
3 {uid: 3, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Invalid type for filter subexpression: expected: String, Array, found: true.", error_code: "invalid_document_filter", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#invalid_document_filter" }, details: { original_filter: true, deleted_documents: Some(0) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: Bool(true) }}
|
||||
4 {uid: 4, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Attribute `id` is not filterable. Available filterable attributes are: `catto`.\n1:3 id = 2", error_code: "invalid_document_filter", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#invalid_document_filter" }, details: { original_filter: "id = 2", deleted_documents: Some(0) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: String("id = 2") }}
|
||||
5 {uid: 5, status: succeeded, details: { original_filter: "catto EXISTS", deleted_documents: Some(1) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: String("catto EXISTS") }}
|
||||
----------------------------------------------------------------------
|
||||
### Status:
|
||||
|
@ -9,7 +9,7 @@ source: index-scheduler/src/lib.rs
|
||||
0 {uid: 0, status: failed, error: ResponseError { code: 200, message: "Document doesn't have a `bork` attribute: `{\"id\":0,\"doggo\":\"jean bob\"}`.", error_code: "missing_document_id", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#missing_document_id" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Document doesn't have a `bork` attribute: `{\"id\":1,\"doggo\":\"jean bob\"}`.", error_code: "missing_document_id", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#missing_document_id" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
2 {uid: 2, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
|
||||
3 {uid: 3, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
|
||||
3 {uid: 3, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
|
||||
4 {uid: 4, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000004, documents_count: 1, allow_index_creation: true }}
|
||||
----------------------------------------------------------------------
|
||||
### Status:
|
||||
|
@ -9,7 +9,7 @@ source: index-scheduler/src/lib.rs
|
||||
0 {uid: 0, status: failed, error: ResponseError { code: 200, message: "Document doesn't have a `bork` attribute: `{\"id\":0,\"doggo\":\"jean bob\"}`.", error_code: "missing_document_id", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#missing_document_id" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Document doesn't have a `bork` attribute: `{\"id\":1,\"doggo\":\"jean bob\"}`.", error_code: "missing_document_id", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#missing_document_id" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
2 {uid: 2, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
|
||||
3 {uid: 3, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
|
||||
3 {uid: 3, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
|
||||
4 {uid: 4, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000004, documents_count: 1, allow_index_creation: true }}
|
||||
----------------------------------------------------------------------
|
||||
### Status:
|
||||
|
@ -7,7 +7,7 @@ source: index-scheduler/src/lib.rs
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
2 {uid: 2, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bloup"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
|
||||
----------------------------------------------------------------------
|
||||
### Status:
|
||||
|
@ -7,8 +7,8 @@ source: index-scheduler/src/lib.rs
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
2 {uid: 2, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bloup"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
2 {uid: 2, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bloup"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
|
||||
----------------------------------------------------------------------
|
||||
### Status:
|
||||
enqueued []
|
||||
|
@ -7,7 +7,7 @@ source: index-scheduler/src/lib.rs
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
2 {uid: 2, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
|
||||
----------------------------------------------------------------------
|
||||
### Status:
|
||||
|
@ -7,7 +7,7 @@ source: index-scheduler/src/lib.rs
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `doggoid`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `doggoid`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
2 {uid: 2, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("doggoid"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
|
||||
3 {uid: 3, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
|
||||
4 {uid: 4, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000004, documents_count: 1, allow_index_creation: true }}
|
||||
|
@ -7,7 +7,7 @@ source: index-scheduler/src/lib.rs
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `doggoid`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `doggoid`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
2 {uid: 2, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("doggoid"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
|
||||
3 {uid: 3, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
|
||||
4 {uid: 4, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000004, documents_count: 1, allow_index_creation: true }}
|
||||
|
@ -7,7 +7,7 @@ source: index-scheduler/src/lib.rs
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `doggoid`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `doggoid`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
2 {uid: 2, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("doggoid"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
|
||||
3 {uid: 3, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
|
||||
4 {uid: 4, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000004, documents_count: 1, allow_index_creation: true }}
|
||||
|
@ -4,6 +4,7 @@ use byte_unit::{Byte, UnitType};
|
||||
use meilisearch_types::document_formats::{DocumentFormatError, PayloadType};
|
||||
use meilisearch_types::error::{Code, ErrorCode, ResponseError};
|
||||
use meilisearch_types::index_uid::{IndexUid, IndexUidFormatError};
|
||||
use meilisearch_types::milli;
|
||||
use meilisearch_types::milli::OrderBy;
|
||||
use serde_json::Value;
|
||||
use tokio::task::JoinError;
|
||||
@ -62,8 +63,11 @@ pub enum MeilisearchHttpError {
|
||||
HeedError(#[from] meilisearch_types::heed::Error),
|
||||
#[error(transparent)]
|
||||
IndexScheduler(#[from] index_scheduler::Error),
|
||||
#[error(transparent)]
|
||||
Milli(#[from] meilisearch_types::milli::Error),
|
||||
#[error("{}", match .index_name {
|
||||
Some(name) if !name.is_empty() => format!("Index `{}`: {error}", name),
|
||||
_ => format!("{error}")
|
||||
})]
|
||||
Milli { error: meilisearch_types::milli::Error, index_name: Option<String> },
|
||||
#[error(transparent)]
|
||||
Payload(#[from] PayloadError),
|
||||
#[error(transparent)]
|
||||
@ -76,6 +80,12 @@ pub enum MeilisearchHttpError {
|
||||
MissingSearchHybrid,
|
||||
}
|
||||
|
||||
impl MeilisearchHttpError {
|
||||
pub(crate) fn from_milli(error: milli::Error, index_name: Option<String>) -> Self {
|
||||
Self::Milli { error, index_name }
|
||||
}
|
||||
}
|
||||
|
||||
impl ErrorCode for MeilisearchHttpError {
|
||||
fn error_code(&self) -> Code {
|
||||
match self {
|
||||
@ -95,7 +105,7 @@ impl ErrorCode for MeilisearchHttpError {
|
||||
MeilisearchHttpError::SerdeJson(_) => Code::Internal,
|
||||
MeilisearchHttpError::HeedError(_) => Code::Internal,
|
||||
MeilisearchHttpError::IndexScheduler(e) => e.error_code(),
|
||||
MeilisearchHttpError::Milli(e) => e.error_code(),
|
||||
MeilisearchHttpError::Milli { error, .. } => error.error_code(),
|
||||
MeilisearchHttpError::Payload(e) => e.error_code(),
|
||||
MeilisearchHttpError::FileStore(_) => Code::Internal,
|
||||
MeilisearchHttpError::DocumentFormat(e) => e.error_code(),
|
||||
|
@ -395,6 +395,7 @@ fn import_dump(
|
||||
for index_reader in dump_reader.indexes()? {
|
||||
let mut index_reader = index_reader?;
|
||||
let metadata = index_reader.metadata();
|
||||
let uid = metadata.uid.clone();
|
||||
tracing::info!("Importing index `{}`.", metadata.uid);
|
||||
|
||||
let date = Some((metadata.created_at, metadata.updated_at));
|
||||
@ -432,7 +433,7 @@ fn import_dump(
|
||||
let reader = DocumentsBatchReader::from_reader(reader)?;
|
||||
|
||||
let embedder_configs = index.embedding_configs(&wtxn)?;
|
||||
let embedders = index_scheduler.embedders(embedder_configs)?;
|
||||
let embedders = index_scheduler.embedders(uid, embedder_configs)?;
|
||||
|
||||
let builder = milli::update::IndexDocuments::new(
|
||||
&mut wtxn,
|
||||
|
@ -185,7 +185,8 @@ pub async fn search(
|
||||
|
||||
let index = index_scheduler.index(&index_uid)?;
|
||||
let features = index_scheduler.features();
|
||||
let search_kind = search_kind(&search_query, &index_scheduler, &index, features)?;
|
||||
let search_kind =
|
||||
search_kind(&search_query, &index_scheduler, index_uid.to_string(), &index, features)?;
|
||||
let permit = search_queue.try_get_search_permit().await?;
|
||||
let search_result = tokio::task::spawn_blocking(move || {
|
||||
perform_facet_search(
|
||||
|
@ -5,7 +5,7 @@ use actix_web::web::Data;
|
||||
use actix_web::{web, HttpRequest, HttpResponse};
|
||||
use deserr::actix_web::{AwebJson, AwebQueryParameter};
|
||||
use deserr::{DeserializeError, Deserr, ValuePointerRef};
|
||||
use index_scheduler::IndexScheduler;
|
||||
use index_scheduler::{Error, IndexScheduler};
|
||||
use meilisearch_types::deserr::query_params::Param;
|
||||
use meilisearch_types::deserr::{immutable_field_error, DeserrJsonError, DeserrQueryParamError};
|
||||
use meilisearch_types::error::deserr_codes::*;
|
||||
@ -107,7 +107,10 @@ pub async fn list_indexes(
|
||||
if !filters.is_index_authorized(uid) {
|
||||
return Ok(None);
|
||||
}
|
||||
Ok(Some(IndexView::new(uid.to_string(), index)?))
|
||||
Ok(Some(
|
||||
IndexView::new(uid.to_string(), index)
|
||||
.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?,
|
||||
))
|
||||
})?;
|
||||
// Won't cause to open all indexes because IndexView doesn't keep the `Index` opened.
|
||||
let indexes: Vec<IndexView> = indexes.into_iter().flatten().collect();
|
||||
|
@ -243,11 +243,19 @@ pub async fn search_with_url_query(
|
||||
let index = index_scheduler.index(&index_uid)?;
|
||||
let features = index_scheduler.features();
|
||||
|
||||
let search_kind = search_kind(&query, index_scheduler.get_ref(), &index, features)?;
|
||||
let search_kind =
|
||||
search_kind(&query, index_scheduler.get_ref(), index_uid.to_string(), &index, features)?;
|
||||
let retrieve_vector = RetrieveVectors::new(query.retrieve_vectors, features)?;
|
||||
let permit = search_queue.try_get_search_permit().await?;
|
||||
let search_result = tokio::task::spawn_blocking(move || {
|
||||
perform_search(&index, query, search_kind, retrieve_vector, index_scheduler.features())
|
||||
perform_search(
|
||||
index_uid.to_string(),
|
||||
&index,
|
||||
query,
|
||||
search_kind,
|
||||
retrieve_vector,
|
||||
index_scheduler.features(),
|
||||
)
|
||||
})
|
||||
.await;
|
||||
permit.drop().await;
|
||||
@ -287,12 +295,20 @@ pub async fn search_with_post(
|
||||
|
||||
let features = index_scheduler.features();
|
||||
|
||||
let search_kind = search_kind(&query, index_scheduler.get_ref(), &index, features)?;
|
||||
let search_kind =
|
||||
search_kind(&query, index_scheduler.get_ref(), index_uid.to_string(), &index, features)?;
|
||||
let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors, features)?;
|
||||
|
||||
let permit = search_queue.try_get_search_permit().await?;
|
||||
let search_result = tokio::task::spawn_blocking(move || {
|
||||
perform_search(&index, query, search_kind, retrieve_vectors, index_scheduler.features())
|
||||
perform_search(
|
||||
index_uid.to_string(),
|
||||
&index,
|
||||
query,
|
||||
search_kind,
|
||||
retrieve_vectors,
|
||||
index_scheduler.features(),
|
||||
)
|
||||
})
|
||||
.await;
|
||||
permit.drop().await;
|
||||
@ -314,6 +330,7 @@ pub async fn search_with_post(
|
||||
pub fn search_kind(
|
||||
query: &SearchQuery,
|
||||
index_scheduler: &IndexScheduler,
|
||||
index_uid: String,
|
||||
index: &milli::Index,
|
||||
features: RoFeatures,
|
||||
) -> Result<SearchKind, ResponseError> {
|
||||
@ -332,7 +349,7 @@ pub fn search_kind(
|
||||
(None, _, None) => Ok(SearchKind::KeywordOnly),
|
||||
// hybrid.semantic_ratio == 1.0 => vector
|
||||
(_, Some(HybridQuery { semantic_ratio, embedder }), v) if **semantic_ratio == 1.0 => {
|
||||
SearchKind::semantic(index_scheduler, index, embedder, v.map(|v| v.len()))
|
||||
SearchKind::semantic(index_scheduler, index_uid, index, embedder, v.map(|v| v.len()))
|
||||
}
|
||||
// hybrid.semantic_ratio == 0.0 => keyword
|
||||
(_, Some(HybridQuery { semantic_ratio, embedder: _ }), _) if **semantic_ratio == 0.0 => {
|
||||
@ -340,13 +357,14 @@ pub fn search_kind(
|
||||
}
|
||||
// no query, hybrid, vector => semantic
|
||||
(None, Some(HybridQuery { semantic_ratio: _, embedder }), Some(v)) => {
|
||||
SearchKind::semantic(index_scheduler, index, embedder, Some(v.len()))
|
||||
SearchKind::semantic(index_scheduler, index_uid, index, embedder, Some(v.len()))
|
||||
}
|
||||
// query, no hybrid, no vector => keyword
|
||||
(Some(_), None, None) => Ok(SearchKind::KeywordOnly),
|
||||
// query, hybrid, maybe vector => hybrid
|
||||
(Some(_), Some(HybridQuery { semantic_ratio, embedder }), v) => SearchKind::hybrid(
|
||||
index_scheduler,
|
||||
index_uid,
|
||||
index,
|
||||
embedder,
|
||||
**semantic_ratio,
|
||||
|
@ -103,8 +103,13 @@ async fn similar(
|
||||
|
||||
let index = index_scheduler.index(&index_uid)?;
|
||||
|
||||
let (embedder_name, embedder, quantized) =
|
||||
SearchKind::embedder(&index_scheduler, &index, &query.embedder, None)?;
|
||||
let (embedder_name, embedder, quantized) = SearchKind::embedder(
|
||||
&index_scheduler,
|
||||
index_uid.to_string(),
|
||||
&index,
|
||||
&query.embedder,
|
||||
None,
|
||||
)?;
|
||||
|
||||
tokio::task::spawn_blocking(move || {
|
||||
perform_similar(
|
||||
|
@ -125,14 +125,28 @@ pub async fn multi_search_with_post(
|
||||
})
|
||||
.with_index(query_index)?;
|
||||
|
||||
let search_kind =
|
||||
search_kind(&query, index_scheduler.get_ref(), &index, features)
|
||||
.with_index(query_index)?;
|
||||
let index_uid_str = index_uid.to_string();
|
||||
|
||||
let search_kind = search_kind(
|
||||
&query,
|
||||
index_scheduler.get_ref(),
|
||||
index_uid_str.clone(),
|
||||
&index,
|
||||
features,
|
||||
)
|
||||
.with_index(query_index)?;
|
||||
let retrieve_vector = RetrieveVectors::new(query.retrieve_vectors, features)
|
||||
.with_index(query_index)?;
|
||||
|
||||
let search_result = tokio::task::spawn_blocking(move || {
|
||||
perform_search(&index, query, search_kind, retrieve_vector, features)
|
||||
perform_search(
|
||||
index_uid_str.clone(),
|
||||
&index,
|
||||
query,
|
||||
search_kind,
|
||||
retrieve_vector,
|
||||
features,
|
||||
)
|
||||
})
|
||||
.await
|
||||
.with_index(query_index)?;
|
||||
|
@ -560,7 +560,8 @@ pub fn perform_federated_search(
|
||||
// use an immediately invoked lambda to capture the result without returning from the function
|
||||
|
||||
let res: Result<(), ResponseError> = (|| {
|
||||
let search_kind = search_kind(&query, index_scheduler, &index, features)?;
|
||||
let search_kind =
|
||||
search_kind(&query, index_scheduler, index_uid.to_string(), &index, features)?;
|
||||
|
||||
let canonicalization_kind = match (&search_kind, &query.q) {
|
||||
(SearchKind::SemanticOnly { .. }, _) => {
|
||||
@ -636,7 +637,8 @@ pub fn perform_federated_search(
|
||||
search.offset(0);
|
||||
search.limit(required_hit_count);
|
||||
|
||||
let (result, _semantic_hit_count) = super::search_from_kind(search_kind, search)?;
|
||||
let (result, _semantic_hit_count) =
|
||||
super::search_from_kind(index_uid.to_string(), search_kind, search)?;
|
||||
let format = AttributesFormat {
|
||||
attributes_to_retrieve: query.attributes_to_retrieve,
|
||||
retrieve_vectors,
|
||||
@ -670,7 +672,10 @@ pub fn perform_federated_search(
|
||||
|
||||
let formatter_builder = HitMaker::formatter_builder(matching_words, tokenizer);
|
||||
|
||||
let hit_maker = HitMaker::new(&index, &rtxn, format, formatter_builder)?;
|
||||
let hit_maker =
|
||||
HitMaker::new(&index, &rtxn, format, formatter_builder).map_err(|e| {
|
||||
MeilisearchHttpError::from_milli(e, Some(index_uid.to_string()))
|
||||
})?;
|
||||
|
||||
results_by_query.push(SearchResultByQuery {
|
||||
federation_options,
|
||||
|
@ -19,7 +19,9 @@ use meilisearch_types::locales::Locale;
|
||||
use meilisearch_types::milli::score_details::{ScoreDetails, ScoringStrategy};
|
||||
use meilisearch_types::milli::vector::parsed_vectors::ExplicitVectors;
|
||||
use meilisearch_types::milli::vector::Embedder;
|
||||
use meilisearch_types::milli::{FacetValueHit, OrderBy, SearchForFacetValues, TimeBudget};
|
||||
use meilisearch_types::milli::{
|
||||
FacetValueHit, InternalError, OrderBy, SearchForFacetValues, TimeBudget,
|
||||
};
|
||||
use meilisearch_types::settings::DEFAULT_PAGINATION_MAX_TOTAL_HITS;
|
||||
use meilisearch_types::{milli, Document};
|
||||
use milli::tokenizer::{Language, TokenizerBuilder};
|
||||
@ -281,35 +283,38 @@ pub enum SearchKind {
|
||||
impl SearchKind {
|
||||
pub(crate) fn semantic(
|
||||
index_scheduler: &index_scheduler::IndexScheduler,
|
||||
index_uid: String,
|
||||
index: &Index,
|
||||
embedder_name: &str,
|
||||
vector_len: Option<usize>,
|
||||
) -> Result<Self, ResponseError> {
|
||||
let (embedder_name, embedder, quantized) =
|
||||
Self::embedder(index_scheduler, index, embedder_name, vector_len)?;
|
||||
Self::embedder(index_scheduler, index_uid, index, embedder_name, vector_len)?;
|
||||
Ok(Self::SemanticOnly { embedder_name, embedder, quantized })
|
||||
}
|
||||
|
||||
pub(crate) fn hybrid(
|
||||
index_scheduler: &index_scheduler::IndexScheduler,
|
||||
index_uid: String,
|
||||
index: &Index,
|
||||
embedder_name: &str,
|
||||
semantic_ratio: f32,
|
||||
vector_len: Option<usize>,
|
||||
) -> Result<Self, ResponseError> {
|
||||
let (embedder_name, embedder, quantized) =
|
||||
Self::embedder(index_scheduler, index, embedder_name, vector_len)?;
|
||||
Self::embedder(index_scheduler, index_uid, index, embedder_name, vector_len)?;
|
||||
Ok(Self::Hybrid { embedder_name, embedder, quantized, semantic_ratio })
|
||||
}
|
||||
|
||||
pub(crate) fn embedder(
|
||||
index_scheduler: &index_scheduler::IndexScheduler,
|
||||
index_uid: String,
|
||||
index: &Index,
|
||||
embedder_name: &str,
|
||||
vector_len: Option<usize>,
|
||||
) -> Result<(String, Arc<Embedder>, bool), ResponseError> {
|
||||
let embedder_configs = index.embedding_configs(&index.read_txn()?)?;
|
||||
let embedders = index_scheduler.embedders(embedder_configs)?;
|
||||
let embedders = index_scheduler.embedders(index_uid, embedder_configs)?;
|
||||
|
||||
let (embedder, _, quantized) = embedders
|
||||
.get(embedder_name)
|
||||
@ -888,6 +893,7 @@ fn prepare_search<'t>(
|
||||
}
|
||||
|
||||
pub fn perform_search(
|
||||
index_uid: String,
|
||||
index: &Index,
|
||||
query: SearchQuery,
|
||||
search_kind: SearchKind,
|
||||
@ -914,7 +920,7 @@ pub fn perform_search(
|
||||
used_negative_operator,
|
||||
},
|
||||
semantic_hit_count,
|
||||
) = search_from_kind(search_kind, search)?;
|
||||
) = search_from_kind(index_uid, search_kind, search)?;
|
||||
|
||||
let SearchQuery {
|
||||
q,
|
||||
@ -1067,17 +1073,27 @@ fn compute_facet_distribution_stats<S: AsRef<str>>(
|
||||
}
|
||||
|
||||
pub fn search_from_kind(
|
||||
index_uid: String,
|
||||
search_kind: SearchKind,
|
||||
search: milli::Search<'_>,
|
||||
) -> Result<(milli::SearchResult, Option<u32>), MeilisearchHttpError> {
|
||||
let (milli_result, semantic_hit_count) = match &search_kind {
|
||||
SearchKind::KeywordOnly => (search.execute()?, None),
|
||||
SearchKind::KeywordOnly => {
|
||||
let results = search
|
||||
.execute()
|
||||
.map_err(|e| MeilisearchHttpError::from_milli(e, Some(index_uid.to_string())))?;
|
||||
(results, None)
|
||||
}
|
||||
SearchKind::SemanticOnly { .. } => {
|
||||
let results = search.execute()?;
|
||||
let results = search
|
||||
.execute()
|
||||
.map_err(|e| MeilisearchHttpError::from_milli(e, Some(index_uid.to_string())))?;
|
||||
let semantic_hit_count = results.document_scores.len() as u32;
|
||||
(results, Some(semantic_hit_count))
|
||||
}
|
||||
SearchKind::Hybrid { semantic_ratio, .. } => search.execute_hybrid(*semantic_ratio)?,
|
||||
SearchKind::Hybrid { semantic_ratio, .. } => search
|
||||
.execute_hybrid(*semantic_ratio)
|
||||
.map_err(|e| MeilisearchHttpError::from_milli(e, Some(index_uid)))?,
|
||||
};
|
||||
Ok((milli_result, semantic_hit_count))
|
||||
}
|
||||
@ -1179,7 +1195,7 @@ impl<'a> HitMaker<'a> {
|
||||
rtxn: &'a RoTxn<'a>,
|
||||
format: AttributesFormat,
|
||||
mut formatter_builder: MatcherBuilder<'a>,
|
||||
) -> Result<Self, MeilisearchHttpError> {
|
||||
) -> milli::Result<Self> {
|
||||
formatter_builder.crop_marker(format.crop_marker);
|
||||
formatter_builder.highlight_prefix(format.highlight_pre_tag);
|
||||
formatter_builder.highlight_suffix(format.highlight_post_tag);
|
||||
@ -1274,11 +1290,7 @@ impl<'a> HitMaker<'a> {
|
||||
})
|
||||
}
|
||||
|
||||
pub fn make_hit(
|
||||
&self,
|
||||
id: u32,
|
||||
score: &[ScoreDetails],
|
||||
) -> Result<SearchHit, MeilisearchHttpError> {
|
||||
pub fn make_hit(&self, id: u32, score: &[ScoreDetails]) -> milli::Result<SearchHit> {
|
||||
let (_, obkv) =
|
||||
self.index.iter_documents(self.rtxn, std::iter::once(id))?.next().unwrap()?;
|
||||
|
||||
@ -1321,7 +1333,10 @@ impl<'a> HitMaker<'a> {
|
||||
.is_some_and(|conf| conf.user_provided.contains(id));
|
||||
let embeddings =
|
||||
ExplicitVectors { embeddings: Some(vector.into()), regenerate: !user_provided };
|
||||
vectors.insert(name, serde_json::to_value(embeddings)?);
|
||||
vectors.insert(
|
||||
name,
|
||||
serde_json::to_value(embeddings).map_err(InternalError::SerdeJson)?,
|
||||
);
|
||||
}
|
||||
document.insert("_vectors".into(), vectors.into());
|
||||
}
|
||||
@ -1367,7 +1382,7 @@ fn make_hits<'a>(
|
||||
format: AttributesFormat,
|
||||
matching_words: milli::MatchingWords,
|
||||
documents_ids_scores: impl Iterator<Item = (u32, &'a Vec<ScoreDetails>)> + 'a,
|
||||
) -> Result<Vec<SearchHit>, MeilisearchHttpError> {
|
||||
) -> milli::Result<Vec<SearchHit>> {
|
||||
let mut documents = Vec::new();
|
||||
|
||||
let dictionary = index.dictionary(rtxn)?;
|
||||
@ -1688,12 +1703,12 @@ fn make_document(
|
||||
displayed_attributes: &BTreeSet<FieldId>,
|
||||
field_ids_map: &FieldsIdsMap,
|
||||
obkv: obkv::KvReaderU16,
|
||||
) -> Result<Document, MeilisearchHttpError> {
|
||||
) -> milli::Result<Document> {
|
||||
let mut document = serde_json::Map::new();
|
||||
|
||||
// recreate the original json
|
||||
for (key, value) in obkv.iter() {
|
||||
let value = serde_json::from_slice(value)?;
|
||||
let value = serde_json::from_slice(value).map_err(InternalError::SerdeJson)?;
|
||||
let key = field_ids_map.name(key).expect("Missing field name").to_string();
|
||||
|
||||
document.insert(key, value);
|
||||
@ -1718,7 +1733,7 @@ fn format_fields(
|
||||
displayable_ids: &BTreeSet<FieldId>,
|
||||
locales: Option<&[Language]>,
|
||||
localized_attributes: &[LocalizedAttributesRule],
|
||||
) -> Result<(Option<MatchesPosition>, Document), MeilisearchHttpError> {
|
||||
) -> milli::Result<(Option<MatchesPosition>, Document)> {
|
||||
let mut matches_position = compute_matches.then(BTreeMap::new);
|
||||
let mut document = document.clone();
|
||||
|
||||
@ -1926,7 +1941,7 @@ fn parse_filter_array(arr: &[Value]) -> Result<Option<Filter>, MeilisearchHttpEr
|
||||
}
|
||||
}
|
||||
|
||||
Ok(Filter::from_array(ands)?)
|
||||
Filter::from_array(ands).map_err(|e| MeilisearchHttpError::from_milli(e, None))
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
|
@ -1446,7 +1446,7 @@ async fn error_document_field_limit_reached_over_multiple_documents() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "A document cannot contain more than 65,535 fields.",
|
||||
"message": "Index `test`: A document cannot contain more than 65,535 fields.",
|
||||
"code": "max_fields_limit_exceeded",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#max_fields_limit_exceeded"
|
||||
@ -2242,7 +2242,7 @@ async fn add_invalid_geo_and_then_settings() {
|
||||
]
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not parse latitude in the document with the id: `\"11\"`. Was expecting a finite number but instead got `null`.",
|
||||
"message": "Index `test`: Could not parse latitude in the document with the id: `\"11\"`. Was expecting a finite number but instead got `null`.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
|
@ -602,7 +602,7 @@ async fn delete_document_by_filter() {
|
||||
"originalFilter": "\"doggo = bernese\""
|
||||
},
|
||||
"error": {
|
||||
"message": "Attribute `doggo` is not filterable. This index does not have configured filterable attributes.\n1:6 doggo = bernese",
|
||||
"message": "Index `EMPTY_INDEX`: Attribute `doggo` is not filterable. This index does not have configured filterable attributes.\n1:6 doggo = bernese",
|
||||
"code": "invalid_document_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_filter"
|
||||
@ -633,7 +633,7 @@ async fn delete_document_by_filter() {
|
||||
"originalFilter": "\"catto = jorts\""
|
||||
},
|
||||
"error": {
|
||||
"message": "Attribute `catto` is not filterable. Available filterable attributes are: `id`, `title`.\n1:6 catto = jorts",
|
||||
"message": "Index `SHARED_DOCUMENTS`: Attribute `catto` is not filterable. Available filterable attributes are: `id`, `title`.\n1:6 catto = jorts",
|
||||
"code": "invalid_document_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_filter"
|
||||
|
@ -95,7 +95,7 @@ async fn error_update_existing_primary_key() {
|
||||
let response = index.wait_task(2).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Index already has a primary key: `id`.",
|
||||
"message": "Index `test`: Index already has a primary key: `id`.",
|
||||
"code": "index_primary_key_already_exists",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#index_primary_key_already_exists"
|
||||
|
@ -711,7 +711,7 @@ async fn filter_invalid_attribute_array() {
|
||||
index.wait_task(task.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass",
|
||||
"message": format!("Index `{}`: Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass", index.uid),
|
||||
"code": "invalid_search_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
|
||||
@ -733,7 +733,7 @@ async fn filter_invalid_attribute_string() {
|
||||
index.wait_task(task.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass",
|
||||
"message": format!("Index `{}`: Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass", index.uid),
|
||||
"code": "invalid_search_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
|
||||
@ -940,7 +940,7 @@ async fn sort_unsortable_attribute() {
|
||||
index.wait_task(response.uid()).await.succeeded();
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Attribute `title` is not sortable. Available sortable attributes are: `id`.",
|
||||
"message": format!("Index `{}`: Attribute `title` is not sortable. Available sortable attributes are: `id`.", index.uid),
|
||||
"code": "invalid_search_sort",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
|
||||
@ -998,7 +998,7 @@ async fn sort_unset_ranking_rule() {
|
||||
index.wait_task(response.uid()).await.succeeded();
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "You must specify where `sort` is listed in the rankingRules setting to use the sort parameter at search time.",
|
||||
"message": format!("Index `{}`: You must specify where `sort` is listed in the rankingRules setting to use the sort parameter at search time.", index.uid),
|
||||
"code": "invalid_search_sort",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
|
||||
@ -1018,8 +1018,8 @@ async fn sort_unset_ranking_rule() {
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn search_on_unknown_field() {
|
||||
let server = Server::new_shared();
|
||||
let index = server.unique_index();
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
let (response, _code) =
|
||||
index.update_settings_searchable_attributes(json!(["id", "title"])).await;
|
||||
index.wait_task(response.uid()).await.succeeded();
|
||||
@ -1031,7 +1031,7 @@ async fn search_on_unknown_field() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
|
||||
"message": "Index `test`: Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
|
||||
"code": "invalid_search_attributes_to_search_on",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_attributes_to_search_on"
|
||||
@ -1044,8 +1044,8 @@ async fn search_on_unknown_field() {
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn search_on_unknown_field_plus_joker() {
|
||||
let server = Server::new_shared();
|
||||
let index = server.unique_index();
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
let (response, _code) =
|
||||
index.update_settings_searchable_attributes(json!(["id", "title"])).await;
|
||||
index.wait_task(response.uid()).await.succeeded();
|
||||
@ -1057,7 +1057,7 @@ async fn search_on_unknown_field_plus_joker() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
|
||||
"message": "Index `test`: Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
|
||||
"code": "invalid_search_attributes_to_search_on",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_attributes_to_search_on"
|
||||
@ -1074,7 +1074,7 @@ async fn search_on_unknown_field_plus_joker() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
|
||||
"message": "Index `test`: Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
|
||||
"code": "invalid_search_attributes_to_search_on",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_attributes_to_search_on"
|
||||
@ -1087,8 +1087,8 @@ async fn search_on_unknown_field_plus_joker() {
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn distinct_at_search_time() {
|
||||
let server = Server::new_shared();
|
||||
let index = server.unique_index();
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
let (task, _) = index.create(None).await;
|
||||
index.wait_task(task.uid()).await.succeeded();
|
||||
|
||||
@ -1097,7 +1097,7 @@ async fn distinct_at_search_time() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(response, @r###"
|
||||
{
|
||||
"message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. This index does not have configured filterable attributes.",
|
||||
"message": "Index `test`: Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. This index does not have configured filterable attributes.",
|
||||
"code": "invalid_search_distinct",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
|
||||
@ -1112,7 +1112,7 @@ async fn distinct_at_search_time() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(response, @r###"
|
||||
{
|
||||
"message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, machin`.",
|
||||
"message": "Index `test`: Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, machin`.",
|
||||
"code": "invalid_search_distinct",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
|
||||
@ -1127,7 +1127,7 @@ async fn distinct_at_search_time() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(response, @r###"
|
||||
{
|
||||
"message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, <..hidden-attributes>`.",
|
||||
"message": "Index `test`: Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, <..hidden-attributes>`.",
|
||||
"code": "invalid_search_distinct",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
|
||||
|
@ -1070,7 +1070,7 @@ async fn federation_one_query_error() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Inside `.queries[1]`: Attribute `title` is not filterable. This index does not have configured filterable attributes.\n1:6 title = toto",
|
||||
"message": "Inside `.queries[1]`: Index `nested`: Attribute `title` is not filterable. This index does not have configured filterable attributes.\n1:6 title = toto",
|
||||
"code": "invalid_search_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
|
||||
@ -1102,7 +1102,7 @@ async fn federation_one_query_sort_error() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Inside `.queries[1]`: Attribute `doggos` is not sortable. This index does not have configured sortable attributes.",
|
||||
"message": "Inside `.queries[1]`: Index `nested`: Attribute `doggos` is not sortable. This index does not have configured sortable attributes.",
|
||||
"code": "invalid_search_sort",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
|
||||
@ -1166,7 +1166,7 @@ async fn federation_multiple_query_errors() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Inside `.queries[0]`: Attribute `title` is not filterable. This index does not have configured filterable attributes.\n1:6 title = toto",
|
||||
"message": "Inside `.queries[0]`: Index `test`: Attribute `title` is not filterable. This index does not have configured filterable attributes.\n1:6 title = toto",
|
||||
"code": "invalid_search_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
|
||||
@ -1198,7 +1198,7 @@ async fn federation_multiple_query_sort_errors() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Inside `.queries[0]`: Attribute `title` is not sortable. This index does not have configured sortable attributes.",
|
||||
"message": "Inside `.queries[0]`: Index `test`: Attribute `title` is not sortable. This index does not have configured sortable attributes.",
|
||||
"code": "invalid_search_sort",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
|
||||
@ -1231,7 +1231,7 @@ async fn federation_multiple_query_errors_interleaved() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Inside `.queries[1]`: Attribute `doggos` is not filterable. This index does not have configured filterable attributes.\n1:7 doggos IN [intel, kefir]",
|
||||
"message": "Inside `.queries[1]`: Index `nested`: Attribute `doggos` is not filterable. This index does not have configured filterable attributes.\n1:7 doggos IN [intel, kefir]",
|
||||
"code": "invalid_search_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
|
||||
@ -1264,7 +1264,7 @@ async fn federation_multiple_query_sort_errors_interleaved() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Inside `.queries[1]`: Attribute `doggos` is not sortable. This index does not have configured sortable attributes.",
|
||||
"message": "Inside `.queries[1]`: Index `nested`: Attribute `doggos` is not sortable. This index does not have configured sortable attributes.",
|
||||
"code": "invalid_search_sort",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
|
||||
|
@ -442,7 +442,7 @@ async fn test_summarized_delete_documents_by_filter() {
|
||||
"originalFilter": "\"doggo = bernese\""
|
||||
},
|
||||
"error": {
|
||||
"message": "Attribute `doggo` is not filterable. This index does not have configured filterable attributes.\n1:6 doggo = bernese",
|
||||
"message": "Index `test`: Attribute `doggo` is not filterable. This index does not have configured filterable attributes.\n1:6 doggo = bernese",
|
||||
"code": "invalid_document_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_filter"
|
||||
|
@ -317,7 +317,7 @@ async fn try_to_disable_binary_quantization() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "`.embedders.manual.binaryQuantized`: Cannot disable the binary quantization.\n - Note: Binary quantization is a lossy operation that cannot be reverted.\n - Hint: Add a new embedder that is non-quantized and regenerate the vectors.",
|
||||
"message": "Index `doggo`: `.embedders.manual.binaryQuantized`: Cannot disable the binary quantization.\n - Note: Binary quantization is a lossy operation that cannot be reverted.\n - Hint: Add a new embedder that is non-quantized and regenerate the vectors.",
|
||||
"code": "invalid_settings_embedders",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_settings_embedders"
|
||||
|
@ -249,7 +249,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `\"0\"`. Missing field `regenerate` inside `.manual`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Missing field `regenerate` inside `.manual`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -278,7 +278,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `\"0\"`. Missing field `regenerate` inside `.manual`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Missing field `regenerate` inside `.manual`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -308,7 +308,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.regenerate`: expected a boolean, but found a string: `\"yes please\"`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.regenerate`: expected a boolean, but found a string: `\"yes please\"`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -337,7 +337,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings`: expected null or an array, but found a boolean: `true`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings`: expected null or an array, but found a boolean: `true`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -366,7 +366,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0]`: expected a number or an array, but found a boolean: `true`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0]`: expected a number or an array, but found a boolean: `true`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -395,7 +395,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0][0]`: expected a number, but found a boolean: `true`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0][0]`: expected a number, but found a boolean: `true`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -436,7 +436,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[1]`: expected a number, but found an array: `[0.2,0.3]`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[1]`: expected a number, but found an array: `[0.2,0.3]`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -464,7 +464,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[1]`: expected an array, but found a number: `0.3`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[1]`: expected an array, but found a number: `0.3`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -492,7 +492,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0][1]`: expected a number, but found a boolean: `true`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0][1]`: expected a number, but found a boolean: `true`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -532,7 +532,7 @@ async fn user_provided_vectors_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `manual`: no vectors provided for document \"40\" and at least 4 other document(s)\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: opt-out for a document with `_vectors.manual: null`",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `manual`: no vectors provided for document \"40\" and at least 4 other document(s)\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: opt-out for a document with `_vectors.manual: null`",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -561,7 +561,7 @@ async fn user_provided_vectors_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `manual`: no vectors provided for document \"42\"\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vector` by `_vectors` in 1 document(s).",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `manual`: no vectors provided for document \"42\"\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vector` by `_vectors` in 1 document(s).",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -590,7 +590,7 @@ async fn user_provided_vectors_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `manual`: no vectors provided for document \"42\"\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vectors.manaul` by `_vectors.manual` in 1 document(s).",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `manual`: no vectors provided for document \"42\"\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vectors.manaul` by `_vectors.manual` in 1 document(s).",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
|
@ -700,7 +700,7 @@ async fn bad_api_key() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `default`: user error: could not authenticate against OpenAI server\n - server replied with `{\"error\":{\"message\":\"Incorrect API key provided: Bearer doggo. You can find your API key at https://platform.openai.com/account/api-keys.\",\"type\":\"invalid_request_error\",\"param\":null,\"code\":\"invalid_api_key\"}}`\n - Hint: Check the `apiKey` parameter in the embedder configuration, and the `MEILI_OPENAI_API_KEY` and `OPENAI_API_KEY` environment variables",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `default`: user error: could not authenticate against OpenAI server\n - server replied with `{\"error\":{\"message\":\"Incorrect API key provided: Bearer doggo. You can find your API key at https://platform.openai.com/account/api-keys.\",\"type\":\"invalid_request_error\",\"param\":null,\"code\":\"invalid_api_key\"}}`\n - Hint: Check the `apiKey` parameter in the embedder configuration, and the `MEILI_OPENAI_API_KEY` and `OPENAI_API_KEY` environment variables",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -743,7 +743,7 @@ async fn bad_api_key() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `default`: user error: could not authenticate against OpenAI server\n - server replied with `{\"error\":{\"message\":\"You didn't provide an API key. You need to provide your API key in an Authorization header using Bearer auth (i.e. Authorization: Bearer YOUR_KEY), or as the password field (with blank username) if you're accessing the API from your browser and are prompted for a username and password. You can obtain an API key from https://platform.openai.com/account/api-keys.\",\"type\":\"invalid_request_error\",\"param\":null,\"code\":null}}`\n - Hint: Check the `apiKey` parameter in the embedder configuration, and the `MEILI_OPENAI_API_KEY` and `OPENAI_API_KEY` environment variables",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `default`: user error: could not authenticate against OpenAI server\n - server replied with `{\"error\":{\"message\":\"You didn't provide an API key. You need to provide your API key in an Authorization header using Bearer auth (i.e. Authorization: Bearer YOUR_KEY), or as the password field (with blank username) if you're accessing the API from your browser and are prompted for a username and password. You can obtain an API key from https://platform.openai.com/account/api-keys.\",\"type\":\"invalid_request_error\",\"param\":null,\"code\":null}}`\n - Hint: Check the `apiKey` parameter in the embedder configuration, and the `MEILI_OPENAI_API_KEY` and `OPENAI_API_KEY` environment variables",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
|
@ -937,7 +937,7 @@ async fn bad_settings() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting a single \"{{embedding}}\", expected `response` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected a sequence",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting a single \"{{embedding}}\", expected `response` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected a sequence",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -976,7 +976,7 @@ async fn bad_settings() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `rest`: runtime error: was expecting embeddings of dimension `2`, got embeddings of dimensions `3`",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `rest`: runtime error: was expecting embeddings of dimension `2`, got embeddings of dimensions `3`",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1127,7 +1127,7 @@ async fn server_returns_bad_request() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: sent a bad request to embedding server\n - Hint: check that the `request` in the embedder configuration matches the remote server's API\n - server replied with `{\"error\":\"Invalid request: invalid type: string \\\"test\\\", expected struct MultipleRequest at line 1 column 6\"}`",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: sent a bad request to embedding server\n - Hint: check that the `request` in the embedder configuration matches the remote server's API\n - server replied with `{\"error\":\"Invalid request: invalid type: string \\\"test\\\", expected struct MultipleRequest at line 1 column 6\"}`",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1194,7 +1194,7 @@ async fn server_returns_bad_request() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `rest`: user error: sent a bad request to embedding server\n - Hint: check that the `request` in the embedder configuration matches the remote server's API\n - server replied with `{\"error\":\"Invalid request: invalid type: string \\\"name: kefir\\\\n\\\", expected struct MultipleRequest at line 1 column 15\"}`",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `rest`: user error: sent a bad request to embedding server\n - Hint: check that the `request` in the embedder configuration matches the remote server's API\n - server replied with `{\"error\":\"Invalid request: invalid type: string \\\"name: kefir\\\\n\\\", expected struct MultipleRequest at line 1 column 15\"}`",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1252,7 +1252,7 @@ async fn server_returns_bad_response() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting the array of \"{{embedding}}\"s, configuration expects `response` to be an array with at least 1 item(s) but server sent an object with 1 field(s)",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting the array of \"{{embedding}}\"s, configuration expects `response` to be an array with at least 1 item(s) but server sent an object with 1 field(s)",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1307,7 +1307,7 @@ async fn server_returns_bad_response() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting item #0 from the array of \"{{embedding}}\"s, expected `response` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected a sequence",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting item #0 from the array of \"{{embedding}}\"s, expected `response` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected a sequence",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1358,7 +1358,7 @@ async fn server_returns_bad_response() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.output`, while extracting a single \"{{embedding}}\", expected `output` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected f32",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.output`, while extracting a single \"{{embedding}}\", expected `output` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected f32",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1421,7 +1421,7 @@ async fn server_returns_bad_response() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.embedding`, while extracting item #0 from the array of \"{{embedding}}\"s, configuration expects `embedding` to be an object with key `data` but server sent an array of size 3",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.embedding`, while extracting item #0 from the array of \"{{embedding}}\"s, configuration expects `embedding` to be an object with key `data` but server sent an array of size 3",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1484,7 +1484,7 @@ async fn server_returns_bad_response() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.output[0]`, while extracting a single \"{{embedding}}\", configuration expects key \"embeddings\", which is missing in response\n - Hint: item #0 inside `output` has key `embedding`, did you mean `response.output[0].embedding` in embedder configuration?",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.output[0]`, while extracting a single \"{{embedding}}\", configuration expects key \"embeddings\", which is missing in response\n - Hint: item #0 inside `output` has key `embedding`, did you mean `response.output[0].embedding` in embedder configuration?",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1846,7 +1846,7 @@ async fn server_custom_header() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: could not authenticate against embedding server\n - server replied with `{\"error\":\"missing header 'my-nonstandard-auth'\"}`\n - Hint: Check the `apiKey` parameter in the embedder configuration",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: could not authenticate against embedding server\n - server replied with `{\"error\":\"missing header 'my-nonstandard-auth'\"}`\n - Hint: Check the `apiKey` parameter in the embedder configuration",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1888,7 +1888,7 @@ async fn server_custom_header() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: could not authenticate against embedding server\n - server replied with `{\"error\":\"thou shall not pass, Balrog\"}`\n - Hint: Check the `apiKey` parameter in the embedder configuration",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: could not authenticate against embedding server\n - server replied with `{\"error\":\"thou shall not pass, Balrog\"}`\n - Hint: Check the `apiKey` parameter in the embedder configuration",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -2031,7 +2031,7 @@ async fn searchable_reindex() {
|
||||
]
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `rest`: error: received unexpected HTTP 404 from embedding server\n - server replied with `{\"error\":\"text not found\",\"text\":\"breed: patou\\n\"}`",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `rest`: error: received unexpected HTTP 404 from embedding server\n - server replied with `{\"error\":\"text not found\",\"text\":\"breed: patou\\n\"}`",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
|
Loading…
Reference in New Issue
Block a user